红外技术2019，Vol.41Issue(1)：78-83,6.
基于扩展Meanshift电气设备发热故障区域提取方法
Fault Region Extraction of Electrical Equipment in Infrared Image by Using an Extended Mean Shift Method
摘要
Abstract
In infrared images, fault regions in electrical equipment often appear at high brilliance. However, some existing methods to extract the region may be influenced by characteristics of infrared imaging, such as low contrast and boundary blur, thus obtaining a larger region than the real fault region. We propose an extended mean shift algorithm by introducing the weight factor associated with the neighboring pixels. To simultaneously improve the efficiency of the clustering method, the original mean shift clustering method to iterate in the image is abandoned. The threshold segmentation mechanism from top to down is merged in the mean shift algorithm. The speed of the clustering pixels is increased, and the fault region is extracted effectively. Experimental results show that the region extraction performance of our method is better than some existing methods and the traditional mean shift clustering method.关键词
均值漂移/电力设备故障/红外图像/阈值/聚类Key words
mean shift/electronical equipment failure/infrared image/thresholding/clustering分类
信息技术与安全科学引用本文复制引用
周正钦,冯振新,周东国,许晓路,谷凯凯..基于扩展Meanshift电气设备发热故障区域提取方法[J].红外技术,2019,41(1):78-83,6.基金项目
国家电网公司总部科技项目(524625160017). （524625160017）
